two_valuable

修改了冈萨雷斯《数字图像处理》中的区域生长法。本函数中含有三种选择种子点的方法：分别依据灰度值，种子点位置，交互式选择单个种子点。(Modified the region growing method described in "Digital Image Processing" . This function contains three options for the method of seed points: based on gray value, the location of the seed points, interactive selection of a single seed point. )

此程序用于伪彩色图象的处理，实现程序的增强功能．(procedure for the pseudo-color image processing, and process enhancements.)

图像拼接的Harris 算法，精确有效，实现图像无缝拼接，多幅图片显示，谢谢，希望得到采纳(image mosaicHarris algorithm for image mosaic, accurate and effective, seamless image mosaic)

TCS3200 RGB颜色采集，可用于检测LED等颜色(TCS3200 RGB color acquisition, can be used to detect LED and other colors)

增强型Lee滤波，附有详细注释，简单易用，参数可调(enhanced LEE filter)

基于小波变换的图像分割算法，它实现了论文 Wavelet Based Bimodal Image Segmentation for Blob Exctraction... 的算法。(This code is a part of work Wavelet Based Bimodal Image Segmentation for Blob Exctraction... .)

自己编的特征选择程序，分别包括用顺序前进法(SFS),顺序后退法(SBS),增l 减r 法(l–r)、SFFS法进行选择的程序(own addendum to the feature selection procedures, including the use of sequential forward (SFS). back order (SBS), by reducing r l (l-r), SFFS method to choose the procedure)

1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,p)/norm(W(:,p)) 8、若W不收敛，返回第5步 9、令p=p+1，若p小于等于m,返回第4步 剩下的应该都能看懂了 基本就是基于负熵最大的快速独立分量分析算法(1, on the center of the observation data, 2, making a mean of 0, the data to whitening-> Z 3, select the number of components to be estimated m, setting the number of iterations p < -1 4, select an initial weight vector (random W, so that the Z dimension of the row vectors of numbers) 5, the use of iteration W (i, p) = mean (z (i, :).* (tanh ((temp) ' * z)))- (mean (1- (tanh ((temp)) ' * z). ^ 2)).* temp (i, 1) to learn W (This formula is used to approximate the negative entropy) 6 with symmetric orthogonal treatments W 7, normalized W (:, p) = W (:, p)/norm (W (:, p)) 8, if W does not converge, return to step 5 9 , so that p = p+1, if p less than or equal m, return to step 4 should be able to read the rest of the basic is based on negative entropy of the largest fast independent component analysis algorithm)

一篇介绍粒子滤波的资料，介绍的很详细，适合研究粒子滤波的初学者，希望对大家有帮助(Introduce a particle filter information on the very detailed study of particle filter is suitable for beginners)

本案例采用基于块匹配的图像拼接流程来执行拼接操作，载入图片文件夹来作为待拼接对象，通过进行图片序列的匹配、融合来得到拼接效果，并分别对灰度图像、彩色图像进行处理。(This case is based on block matching process to perform image stitching splicing operation, load images folder as an object to be spliced, by matching the fusion image sequence to get the mosaic effect, respectively, on the gray image, color image processing .)